Package: EMDSSAForecast 0.1.0

Prabhat Kumar

EMDSSAForecast: Hybrid EMD-SSA Forecasting with Artificial Neural Networks for Time Series

Implements a hybrid empirical mode decomposition, singular spectrum analysis, and artificial neural network forecasting framework for time series data. The framework extracts the trend from the first intrinsic mode function using singular spectrum analysis, forecasts the extracted trend and remaining decomposition components using artificial neural networks, and combines the component forecasts to obtain the final forecast. For methodological details, refer to Kumar et al. (2026) <doi:10.1007/s10791-026-10076-2>.

Authors:Prabhat Kumar [aut, cre], Girish Kumar Jha [aut], Rajeev Ranjan Kumar [aut], Santosha Rathod [aut], R N Singh [aut]

EMDSSAForecast_0.1.0.tar.gz
EMDSSAForecast_0.1.0.zip(r-4.7-any)EMDSSAForecast_0.1.0.zip(r-4.6-any)
EMDSSAForecast_0.1.0.tar.gz(r-4.7-any)EMDSSAForecast_0.1.0.tar.gz(r-4.6-any)
EMDSSAForecast_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
EMDSSAForecast/json (API)

# Install 'EMDSSAForecast' in R:
install.packages('EMDSSAForecast', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 9 exports 37 dependencies

Last updated from:3aded3aa5a. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK129
source / vignettesOK159
linux-releaseOK141
windows-develOK85
windows-releaseOK67
wasm-releaseOK124

Exports:accuracy_metricsannTSforecastemd_decomposeemd_ssa_annTSforecastplot_imfsplot_ssa_trendreconstruct_forecastssa_trendtune_emd_ssa_annTSforecast

Dependencies:clicolorspacecpp11Derivfarverforecastfracdiffgenericsggplot2gluegtableisobandlabelinglatticelifecyclelmtestmagrittrMASSneuralnetnlmennetR6RColorBrewerRcppRcppArmadillorlangRlibeemdRssaS7scalessvdtimeDateurcavctrsviridisLitewithrzoo